Lauren H. Cohen

Lauren Cohen is a Professor in the Finance area at Harvard Business School, an Editor of Management Science, and a Faculty Research Fellow at the National Bureau of Economic Research. He has also served on the editorial boards of the Review of Financial Studies and the Review of Asset Pricing Studies. Prior to joining HBS, he was an Assistant Professor of Finance at Yale University, in the School of Management, where he was on the faculty from 2005-2007.

His award-winning research has been published in the top journals in Finance and Economics. It is also frequently described in various media outlets including The Wall Street Journal, The New York Times, The Washington Post, Fortune, and Forbes. He is the recipient of a National Science Foundation (NSF) Early Career Development Award for his research agenda on Relationships in Finance. Dr. Cohen received a PhD in finance and an MBA from the University of Chicago in 2005. He earned dual undergraduate degrees from the University of Pennsylvania - a BSE from the Wharton School and a BA in economics from the College of Arts & Sciences in 2001. He serves on the advisory board of Quadriserv, Inc.

Featured Work

We provide theoretical and empirical evidence on the evolution and impact of non-practicing entities (NPEs) in the intellectual property space. Heterogeneity in innovation, given a cost of commercialization, results in NPEs that choose to act as "patent trolls" that chase operating firms' innovations even if those innovations are not clearly infringing on the NPEs' patents. We support these predictions using a novel, large dataset of patents targeted by NPEs. We show that NPEs on average target firms that are flush with cash (or have just had large positive cash shocks). Furthermore, NPEs target firm profits arising from exogenous cash shocks unrelated to the allegedly infringing patents. We next show that NPEs target firms irrespective of the closeness of those firms' patents to the NPEs', and that NPEs typically target firms that are busy with other (non-IP related) lawsuits or are likely to settle. Lastly, we show that NPE litigation has a negative real impact on the future innovative activity of targeted firms.

We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.

This paper employs a new empirical approach for identifying the impact of government spending on the private sector. Our key innovation is to use changes in congressional committee chairmanship as a source of exogenous variation in state-level federal expenditures. In doing so, we show that fiscal spending shocks appear to significantly dampen corporate sector investment and employment activity. This retrenchment follows both Senate and House committee chair changes, occurs in large and small firms and within large and small states, and is most pronounced among geographically-concentrated firms. The effects are economically meaningful and the mechanism - entirely distinct from the more traditional interest rate and tax channels - suggests new considerations in assessing the impact of government spending on private sector economic activity.

Publications

We demonstrate that legislation has a simple, yet previously undetected impact on stock prices. Exploiting the voting record of legislators whose constituents are the affected industries, we show that the votes of these "interested" legislators capture important information seemingly ignored by the market. A long-short portfolio based on these legislators' views earns abnormal returns of over 90 basis points per month following the passage of legislation. Industries that we classify as beneficiaries of legislation experience significantly more positive earnings surprises and positive analyst revisions in the months following passage of the bill, as well as significantly higher future sales and profitability. We show that the more complex the legislation, the more difficulty the market has in assessing the impact of these bills; further, the more concentrated the legislator's interest in the industry, the more informative are her votes for future returns.

We demonstrate that personal connections amongst U.S. politicians have a significant impact on Senate voting behavior. Networks based on alumni connections between politicians are consistent predictors of voting behavior. We estimate sharp measures that control for common characteristics of the network, as well as heterogeneous impacts of a common network characteristic across votes. We find that the effect of alumni networks is close to 60% as large as the effect of state-level considerations. The network effects we identify are stronger for more tightly linked networks, and at times when votes are most valuable. We show that politicians use school ties as a mechanism to engage in vote trading ("logrolling"), and that alumni networks help facilitate the procurement of discretionary earmarks.

We demonstrate that a firm's ability to innovate is predictable, persistent, and relatively simple to compute, and yet the stock market ignores the implications of past successes when valuing future innovation. We show that two firms that invest the exact same in research and development (R&D) can have quite divergent, but predictably divergent, future paths. Our approach is based on the simple premise that while future outcomes associated with R&D investment are uncertain, the past track records of firms may give insight into their potential for future success. We show that a long-short portfolio strategy that takes advantage of the information in past track records earns abnormal returns of roughly 11% per year. Importantly, these past track records also predict divergent future real outcomes in patents, patent citations, and new product innovations.

We provide evidence that firms appoint independent directors who are overly sympathetic to management, while still technically independent according to regulatory definitions. We explore a subset of independent directors for whom we have detailed, micro-level data on their views regarding the firm prior to being appointed to the board: sell-side analysts who are subsequently appointed to the boards of companies they previously covered. We find that boards appoint overly optimistic analysts who are also poor relative performers. The magnitude of the optimistic bias is large: 82.0% of appointed recommendations are strong-buy/buy recommendations, compared to 56.9% for all other analyst recommendations. We also show that appointed analysts' optimism is stronger at precisely those times when firms' benefits are larger. Lastly, we find that appointing firms are more likely to have management on the board nominating committee, appear to be poorly governed, and increase earnings management and CEO compensation following these board appointments.

Using a simple empirical strategy, we decode the information in insider trading. Exploiting the fact that insiders trade for a variety of reasons, we show that there is predictable, identifiable "routine" insider trading that is not informative for the future of firms. Stripping away the trades of routine insiders leaves a set of information-rich trades by "opportunistic" insiders that contain all the predictive power in the insider trading universe. A portfolio strategy that focuses solely on opportunistic traders yields value-weighted abnormal returns of 82 basis points per month, while the abnormal returns associated with routine traders are essentially zero. Further, opportunistic insiders predict future firm-specific news, as well as announcement returns around future analyst forecasts, management forecasts, and earnings announcements, while routine traders do not. The most informed opportunistic traders are local non-senior insiders, who come from geographically concentrated, poorly governed firms. Lastly, opportunistic traders are significantly more likely to have SEC enforcement action taken against them and reduce their trading following waves of SEC insider trading enforcement.

We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.

This paper employs a new empirical approach for identifying the impact of government spending on the private sector. Our key innovation is to use changes in congressional committee chairmanship as a source of exogenous variation in state-level federal expenditures. In doing so, we show that fiscal spending shocks appear to significantly dampen corporate sector investment and employment activity. This retrenchment follows both Senate and House committee chair changes, occurs in large and small firms and within large and small states, and is most pronounced among geographically concentrated firms. The effects are economically meaningful and the mechanism-entirely distinct from the more traditional interest rate and tax channels-suggests new considerations in assessing the impact of government spending on private sector economic activity.

We study the impact of social networks on agents' ability to gather superior information about firms. Exploiting novel data on the educational backgrounds of sell-side equity analysts and senior officers of firms, we test the hypothesis that analysts' school ties to senior officers impart comparative information advantages in the production of analyst research. We find evidence that analysts outperform on their stock recommendations when they have an educational link to the company. A simple portfolio strategy of going long the buy recommendations with school ties and going short buy recommendations without ties earns returns of 6.60% per year. We test whether Regulation FD, targeted at impeding selective disclosure, constrained the use of direct access to senior management. We find a large effect: pre-Reg FD the return premium from school ties was 9.36% per year, while post-Reg FD the return premium was nearly zero and insignificant. In contrast, in an environment that did not change selective disclosure regulation (the U.K.), the analyst school-tie premium has remained large and significant over the entire sample period.

We explore a new channel for attracting inflows using a unique dataset of corporate 401(k) retirement plans and their mutual fund family trustees. Families secure substantial inflows by being named the trustee of a 401(k) plan. We find that family trustees significantly overweight their 401(k) client firm's stock. Trustee overweighting is more pronounced when the relationship is more valuable to the trustee family, and it is concentrated in those funds that receive the greatest benefit from the inflows. When other mutual funds are selling the client firm's stock, the trustee does the opposite and significantly increases its holdings of the client. This overweighting is not explained by superior information. We also quantify the flow benefit to the trustee mutual funds of being included in the client firm's 401(k) plan and find that this inclusion has an economically and statistically large, positive effect on inflows.

I evaluate the effect of loyalty on individuals' portfolio choice using a unique dataset of retirement contributions. I exploit the statutory difference that in 401(k) plans stand alone employees can invest directly in their division, while conglomerate employees must invest in the entire firm, including all unrelated divisions. Consistent with loyalty, employees of stand alone firms invest 10 percentage points (75%) more in company stock than conglomerate employees. Support is also found using variation in loyalty between different groups of employees, both across and within firms. The cost to employees of loyalty is large, and can amount to nearly a 20 percent loss in retirement income.

This paper uses social networks to identify information transfer in security markets. We focus on connections between mutual fund managers and corporate board members via shared education networks. We find that portfolio managers place larger bets on firms they are connected to through their network, and perform significantly better on these holdings relative to their non-connected holdings. A replicating portfolio of connected stocks outperforms a replicating portfolio of non-connected stocks by up to 7.8% per year. Returns are concentrated around corporate news announcements, consistent with mutual fund managers gaining an informational advantage through the education networks. Our results suggest that social networks may be an important mechanism for information flow into asset prices.

This paper finds evidence of return predictability across economically linked firms. We test the hypothesis that in the presence of investors subject to attention constraints, stock prices do not promptly incorporate news about economically related firms, generating this return predictability across assets. We use a dataset of firms' principal customers to identify a set of economically related firms, and show that stock prices do not incorporate news involving related firms, generating predictable subsequent price moves. A long/short equity strategy based on this effect yields monthly alphas of over 150 basis points, or over 18 percent per year.

Using proprietary data on stock loan fees and quantities from a large institutional investor, we examine the link between the shorting market and stock prices. Employing a unique identification strategy, we isolate shifts in the supply and demand for shorting. We find that shorting demand is an important predictor of future stock returns: An increase in shorting demand leads to negative abnormal returns of 2.98% in the following month. Second, we show that our results are stronger in environments with less public information flow, suggesting that the shorting market is an important mechanism for private information revelation.

We show that increased litigation risk has driven innovators to shield themselves by shifting innovation out of industry and into universities. We show both theoretically and empirically that litigation by Non-Practicing Entities (NPEs) pushes innovation to spaces with reduced litigation threat. Innovation has shifted into universities (and away from public and private firms) in exactly those industries with the most aggressive NPE litigation, precisely following extensive NPE litigation. The extent of innovation shielding is large and significant. An increase of 100 NPE lawsuits in an industry shifts up the university share of innovation by roughly 70% in subsequent years (t=5.34).

We develop a theoretical model of, and provide the first large-sample evidence on, the behavior and impact of non-practicing entities (NPEs) in the intellectual property space. Our model shows that NPE litigation can reduce infringement and support small inventors. However, the model also shows that as NPEs become effective at bringing frivolous lawsuits, the resulting defense costs inefficiently crowd out some firms that, absent NPEs, would produce welfare-enhancing innovations without engaging in infringement. Our empirical analysis shows that on average, NPEs appear to behave as opportunistic patent trolls. NPEs sue cash-rich firms—a one standard deviation increase in cash holdings increases a firm's chance of being targeted by NPE litigation more than fourfold. We find moreover that NPEs target cash unrelated to the alleged infringement at essentially the same frequency as they target cash related to the alleged infringement. By contrast, cash is neither a key driver of intellectual property lawsuits by practicing entities (e.g., IBM and Intel), nor of any other type of litigation against firms. The cash-targeting behavior we observe is driven by large aggregator NPEs, and is not the behavior of small innovators. We find further suggestive evidence of NPE opportunism, such as forum shopping and targeting of firms that may have reduced ability to defend themselves against litigation. Finally, we find that NPE litigation has a real negative impact on innovation at targeted firms: firms substantially reduce their innovative activity after settling with NPEs (or losing to them in court).

Much like states that rely on government spending, certain firms rely on the government for a substantial share of their revenues. Exploiting the statutory requirement that forces firms to list the identities of their major customers, we identify and examine the set of firms whose major customers are listed as government entities. We employ an identification strategy that exploits government contract bid protests in order to identify the causal impact of government sales on future firm outcomes, and find that government-linked firms invest less in physical and intellectual capital, and have lower future sales growth.

We explore a subtle but important mechanism through which firms manipulate their information environments. We show that firms control information flow to the market through their specific organization and choreographing of earnings conference calls. Firms that "cast" their conference calls by disproportionately calling on bullish analysts tend to underperform in the future. Firms that call on more favorable analysts experience more negative future earnings surprises and more future earnings restatements. A long-short portfolio that exploits this differential firm behavior earns abnormal returns of up to 101 basis points per month. Further, firms that cast their calls have higher accruals leading up to call, barely exceed/meet earnings forecasts on the call that they cast, and in the quarter directly following their casting tend to issue equity and have significantly more insider selling.

We explore a new mechanism through which investors take correlated shortcuts. Specifically, we exploit a regulatory provision governing firm classification into industries: A firm's industry classification is determined by the segment that has the majority of sales. We find strong evidence that investors overly rely on this primary industry classification. Firms just above the industry classification cutoff have significantly higher betas with respect to, as well as more sector mutual fund holdings and analyst coverage from, that industry, compared to nearly identical firms just below the cutoff. We then show that managers undertake specific actions to exploit investor shortcuts. Firms around the discontinuity point of 50% sales are significantly more likely to have just over 50% of sales from a "favorable" industry. Further, these firms just over the cutoff have significantly lower profit margins and inventory growth compared to other firms in the same industries, consistent with these firms slashing prices to increase sales. These same firms, however, do not exhibit different behaviors in any other aspect of their business (e.g., CapEx or R&D), suggesting that it is not a firm-wide shift of focus. Last, firms garner tangible benefits from switching into favorable industries, such as engaging in significantly more SEOs and stock-financed M&As.

We demonstrate that simply by using the ethnic makeup surrounding a firm's location, we can predict, on average, which trade links are valuable for firms. Using customs and port authority data on the international shipments of all U.S. publicly-traded firms, we show that firms are significantly more likely to trade with countries that have a large resident population near their firm headquarters. We use the formation of World War II Japanese Internment Camps to isolate exogenous shocks to local ethnic populations, and identify a causal link between local networks and firm trade. We also show that firms are more likely to acquire target firms, and report increased segment sales, in countries to which they are connected. Firms that exploit their local networks also see significant increases in future sales growth and profitability. In sum, our results document a surprisingly large impact of immigrants' role as economic conduits for firms in their new countries.

In the summer of 2008, AQR Capital Management was considering the launch of a new hedge fund strategy. The proposed DELTA portfolio would offer investors exposure to a basket of nine major hedge fund strategies. The DELTA strategy would be innovative in two ways. First, in terms of its structure, AQR would implement these underlying strategies using a well-defined investment process, with the goal being to deliver exposure to a well-diversified portfolio of hedge fund strategies. Second, it terms of its fees, the new DELTA strategy would charge investors relatively lower fees: 1% management fees plus 10% of performance over a cash hurdle (or, alternatively, a management fee of 2% only). This fee structure was low relative to the industry, where 2% management fees plus 20% of performance, often with no hurdle, was standard.

This case examines Dimensional Fund Advisors (DFA)'s decision to enter the retirement market with their new "Dimensional Managed DC" product, a complete retirement solution that aimed to provide investors with what they really wanted: the same standard of living in retirement that they had while working. The case considers the challenges of entering the fiercely competitive retirement market, introduces students to the large literature on the behavioral biases of individual investors, and asks students to evaluate an innovative new financial product designed to automate the process of retirement investing.

AQR is a hedge fund based in Greenwich, Connecticut, that is considering offering a wholly new line of product to retail investors, namely the ability to invest in the price phenomenon known as momentum. There is a large body of empirical evidence supporting momentum across many different asset classes and countries. However, up until this point, momentum was a strategy employed nearly exclusively by hedge funds, and thus not an available investment strategy to most individual investors. This case highlights the difficulties in implementing this “mutual fund-itizing” of a hedge fund product, along with the challenges that the open-end and regulatory features that a mutual fund poses to many successful strategies implemented in other contexts. In addition, it gives students the ability to calculate and interpret various horizons of correlations between many popular investment strategies using long time-series data and then thinking about the potential complementarities of strategies from a portfolio construction context.

This is a (B) case for AQR's Momentum Funds. It follows the first year of performance of the funds after launching, and gives students a critical inflection point for analyzing the nascent stages of a new product launch and the potential path dependence of the product depending on initial returns. It allows students to wrestle with the way forward given these conditions, and how (if at all) it changes their views, pitch, and perspective on the strategy, and traditional long-short strategies more generally.

Miracle Life is a firm with a unique setup and organizational structure. Specifically, it is a network marketing firm, also known as multi-level marketing (MLM) firm, which utilizes a large distributor base and depends on this individual distributor base to sell its products, giving explicit incentives for these individual distributors to both sell its products and sign up other distributors. The case gives students the opportunity to take the basic framework of Discounted Cash Flow (DCF) Analysis and apply it to two unique perspectives of an identical problem. The students will then use this DCF approach to rationalize observed stock prices, connecting the two, and further reconcile how a company's future plan for growth, and the plausibility of this plan, has implications jointly for DCF and stock prices.

PlanetTran is an environmentally-friendly car service that utilizes a fleet of hybrid cars in providing livery service to corporations and individuals. The founder, Seth Riney, is evaluating outside funding options in order to expand the company, and has met several local venture capital (VC) firms, Riney must decide if the dilution he would have to undergo in order to accept a substantial capital investment was worth the added upside to the company that both he and the VCs envisioned.

Tottenham Hotspur Football Club is a publicly-owned professional soccer team based in London, England. The club's chairman, Daniel Levy, is contemplating a significant investment in physical assets, including the development of a new stadium as well as the acquisition of a new player. The team must decide if the expected cash flows associated with adding the stadium, the player, or both, warrant the considerable required investments in these assets.

Research Summary

Awards & Honors

Winner of a National Science Foundation Faculty Early Career Development (CAREER) Award for 2009-2014.

Won the 2007 Smith Breeden Distinguished Paper Prize for the Best Paper in the Journal of Finance for his paper with Karl Diether and Christopher Malloy, “Supply and Demand Shifts in the Shorting Market” (October 2007).

Won the 2008 Smith Breeden Prize for a distinguished paper in the Journal of Finance for his paper with Andrea Frazzini, “Economic Links and Predictable Returns” (Journal of Finance, August 2008).

Won the 2010 Smith Breeden Distinguished Paper Honor for the Best Paper in the Journal of Finance for his paper with Christopher Malloy and Andrea Frazzini, “Sell-Side School Ties” (August 2010).

Presented testimony on the “Impacts of Government Spending” to the Committee on Transportation and Infrastructure, United States House of Representatives, Sept 29, 2010.

Won the 2007 Society of Quantitative Analysts Award for Best Paper in Quantitative Investments from the Western Finance Association for the paper with Breno Schmidt, “Attracting Flows by Attracting Big Clients” (Journal of Finance, October 2009).

Won the 2006 Barclays Global Investors Best Paper Prize, Asset Allocation Symposium, European Finance Association, for the paper with Breno Schmidt, “Attracting Flows by Attracting Big Clients” (Journal of Finance, October 2009).

Won the 2007 Barclays Global Investors Best Paper Prize, Asset Allocation Symposium, European Finance Association, for the paper with Andrea Frazzini and Christopher Malloy, “The Small World of Investing: Board Connections and Mutual Fund Returns” (Journal of Political Economy, October 2008).

Winner of the 2010 Best Paper Prize from the Center for Research in Security Prices Forum for "Complicated Firms" (with Dong Lou, Journal of Financial Economics, May 2012).

Won the 2011 Richard A. Crowell Memorial Award, First Prize, from PanAgora Asset Management’s Quantitative Research Institute for the best paper in the field of quantitative investment for his paper with Dong Lou, “Complicated Firms” (Journal of Financial Economics, May 2012).

Winner of the 2010 First Prize in the Istanbul Stock Exchange 25th Anniversary Best Paper Competition for "Complicated Firms" (with Dong Lou, Journal of Financial Economics, May 2012).

Won the 2006 First Prize in the Chicago Quantitative Alliance Academic Paper Competition for the paper (with Andrea Frazzini) "Economic Links and Predictable Returns" (Journal of Finance, August 2008).

Winner of the 2014 Crowell Memorial Prize for Best Paper on Quantitative Investing from PanAgora Asset Management for "Playing Favorites: How Firms Prevent the Revelation of Bad News" (with Dong Lou and Christopher J. Malloy, 2014).

Winner of the 2013 Fama-DFA Second Place Prize for the Best Paper Published in the Journal of Financial Economics in the Areas of Capital Markets and Asset Pricing for "Legislating Stock Prices" (with Karl Diether and Christopher Malloy, December 2013).